Use this URL to cite or link to this record in EThOS: http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.633699
Title: An objective Bayesian approach for discrete scenarios
Author: Villa, Cristiano
Awarding Body: University of Kent
Current Institution: University of Kent
Date of Award: 2013
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Abstract:
Objective prior distributions represent a fundamental part of Bayesian inference. Although several approaches for continuous parameter spaces have been developed, Bayesian theory lacks of a general method that allows to obtain priors for the discrete case. In the present work we propose a novel idea, based on losses, to derive objective priors for discrete parameter spaces. We objectively measure the worth of each parameter values, and link it to the prior probability by means of the self information loss function. The worth is measured by taking into consideration the surroundings of each element of the parameter space. Bayes theorem is then re-interpreted, where prior and posterior beliefs are not expressed as probabilities, but as losses. The approach allows to retain meaning from the beginning to the end of the Bayesian updating process. The prior distribution obtained with the above approach is identified as the t-Walker prior. We illustrate the approach by applyi~t.,to various scenarios. We derive objective priors for five specific models: a population size model, the Hypergeometric and multivariate Hypergeometric models, the Binomial-Beta model, and the Binomial model. We also derive the Villa- Walker prior for the number of degrees of freedom of a t distribution. An important result in this last case, is that the objective prior has to be truncated.
Supervisor: Not available Sponsor: Not available
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral
EThOS ID: uk.bl.ethos.633699  DOI: Not available
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